Uncertainty in Artificial Intelligence
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Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials
Barry Cobb, Prakash Shenoy
Abstract:
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials can be used to approximate utility functions. This paper introduces MTE influence diagrams, which can represent decision problems without restrictions on the relationships between continuous and discrete chance variables, without limitations on the distributions of continuous chance variables, and without limitations on the nature of the utility functions. In MTE influence diagrams, all probability distributions and the joint utility function (or its multiplicative factors) are represented by MTE potentials and decision nodes are assumed to have discrete state spaces. MTE influence diagrams are solved by variable elimination using a fusion algorithm.
Keywords: null
Pages: 85-93
PS Link:
PDF Link: /papers/04/p85-cobb.pdf
BibTex:
@INPROCEEDINGS{Cobb04,
AUTHOR = "Barry Cobb and Prakash Shenoy",
TITLE = "Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials",
BOOKTITLE = "Proceedings of the Twentieth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-04)",
PUBLISHER = "AUAI Press",
ADDRESS = "Arlington, Virginia",
YEAR = "2004",
PAGES = "85--93"
}


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